Two key brain networks emerged as the primary engines of this phenomenon: the Default Mode Network (DMN) and the visual network. Each network accounted for more than 20 percent of the machine-learning model’s ability to discriminate between contexts.
"The default mode network is strongly associated with the sense of self: daydreaming, mind wandering, thinking about yourself. It’s often been called the narrative self," Stoliker explains. "On the other end of this gradient, more externally oriented, is the visual system."
In a sober state, the Default Mode Network and the visual system operate with a high degree of independence, establishing a clear neural boundary between internal self-reflection and external visual perception. Under psilocybin, however, this functional distinction blurred dramatically.
Because the self-referential DMN and the externally focused visual network began operating along a shared continuum, the brain lost its traditional mechanics for separating internal thought from external stimuli. The researchers suggest this neural convergence directly mirrors the subjective experience reported by many volunteers: a sense that the boundary between the observer and the environment has dissolved—a psychological state Stoliker terms "embeddedness."
"Theoretically, we could suggest that psychedelics are temporarily altering the organization of brain networks that ordinarily help maintain this separation that we experience," he says. "It really challenges the idea of whether the internal world and external world are separate and highlights the idea that the brain may be responsible for constructing both."
Tuning the Room
The clinical implications of these findings extend well beyond theoretical neuroscience. The day after their scanning sessions, participants completed comprehensive psychological evaluations measuring shifts in their feelings of connection—to themselves, to others, and to the natural world—alongside metrics tracking peace, acceptance, and creativity on a scale ranging from -100 to +100.
"For the vast majority of our participants, we found they had positive psychological changes the next day," Stoliker says.
Notably, the magnitude of these positive psychological improvements correlated directly with how accurately the machine-learning classifier had been able to distinguish between the four context settings in that participant’s brain scans. The more organized and context-responsive the brain became under psilocybin, the greater the lasting emotional benefit reported the following day.
In therapeutic settings, clinicians have long emphasized the importance of "set and setting"—the patient’s mindset and physical environment—during psychedelic-assisted psychotherapy. The findings from PsiConnect suggest that environmental context is not merely a passive background factor that puts patients at ease, but an active driver that mechanically reshapes brain network architecture during the trip.
If external conditions directly structure neural trajectories, then variables like music selection, room lighting, visual decorations, and verbal instructions act as functional clinical dials. In the future, therapists might deliberately adjust these variables in real time to optimize therapeutic outcomes for specific mental health conditions.
However, Stoliker and his co-authors emphasize that several crucial questions remain before these findings can be directly translated into clinical practice.
First, subjective individual experiences remain complex: two participants who receive identical "embeddedness" scores on brain scans can still report markedly different personal journeys. Second, the PsiConnect study was conducted entirely on healthy adult volunteers. Additional research is necessary to determine whether patients suffering from major depressive disorder, post-traumatic stress disorder (PTSD), or severe anxiety exhibit the same dynamic neural clustering when exposed to psilocybin.
Finally, scientists do not yet know the precise prescription for tuning these environmental inputs. "That’s a future avenue where we need more research to determine exactly what conditions should be optimized, and for who," Stoliker notes. "It’s quite possible we would want to take different approaches for each individual, or depending on what their diagnosis is."
Nevertheless, by demonstrating that advanced AI tools can reveal structured geometry beneath what long appeared to be random neural noise, the study opens a new chapter in psychedelic science. "Still," Stoliker concludes, "finding this level of organization hidden underneath that disorder and chaos has some really good explanatory value."
